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Rare, Relevant, and Still Wrong: How Memory Fails LLM Group Decisions

Paper recorded by Signals 4 on 2026-10-27 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-27 on arXiv · recorded by Signals 4 on 2026-10-28

Category: cs.AI · 人工智能 · first seen 2026-10-28

Abstract

When an LLM group's discussion is compressed into a short memory for a final decision maker, what should the memory keep? Two natural heuristics keep the rarest claims or the claims relevant to the decision criteria. On hidden-profile tasks both look attractive, because how widely a fact is held is confounded with whether it helps. We introduce CrossProfile, a diagnostic benchmark of 60 templates

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#108 most recent of 940 cs.AI papers we have recorded · ↑ newer: What Improves During Pretraining? Tracking Knowledge Acquisition with · ↓ older: VideoLVR: Latent Visual Reasoning over Grounded Video Evidence
Cite this page: Rare, Relevant, and Still Wrong: How Memory Fails LLM Group Decisions: the #108 most recent of 940 cs.AI papers we have recorded (as of 2026-10-27). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/rare-relevant-and-still-wrong-how-memory-fails-llm-group-decisions.html
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